# [1]孙国强,卫志农,叶芳,等.基于联络线功率限制的多平衡机状态估计算法[J].东南大学学报(自然科学版),2010,40(5):957-962.[doi:10.3969/j.issn.1001-0505.2010.05.015] 　Sun Guoqiang,Wei Zhinong,Ye Fang,et al.State estimation algorithm for multi-balancing machines based on power limits in interconnecting lines[J].Journal of Southeast University (Natural Science Edition),2010,40(5):957-962.[doi:10.3969/j.issn.1001-0505.2010.05.015] 点击复制 基于联络线功率限制的多平衡机状态估计算法() 分享到： var jiathis_config = { data_track_clickback: true };

40

2010年第5期

957-962

2010-09-20

## 文章信息/Info

Title:
State estimation algorithm for multi-balancing machines based on power limits in interconnecting lines

1 河海大学能源与电气学院,南京 210098; 2 云南电力调度中心,昆明 650011
Author(s):
1 College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, China
2 Yunnan Electric Power Dispatching Center, Kunming 650011, China

Keywords:

TM743
DOI:
10.3969/j.issn.1001-0505.2010.05.015

Abstract:
To meet the requirements of multi-balancing machines’ settings and power limitations in interconnecting lines, the measurement functions and the corresponding Jacobian matrix are deduced. And two state estimation algorithms, the entire algorithm and the distributed algorithm, for multi-balancing machines incorporating power limits in interconnecting lines are proposed. In the entire algorithm, the transmission power limits are considered as equality constraints. The calculation model is derived by the Lagrange multiplier method and the state variables in each region are calculated by iterations. In the distributed algorithm, each region is treated separately based on the overlapped distributed method, and the boundary equality constrains are included into the corresponding objective functions. Then,the distributed state estimation is implemented by the Lagrange multiplier method. Numerical examples of IEEE-14, IEEE-30 and IEEE-57 bus test systems are given. The simulation results show that the proposed models are correct and effective. In addition, the calculation speed and precision of the distributed algorithm are higher than those of the entire algorithm.

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